In the context of SI system evaluation, the Turing Test [1]} and the Consensual Assessment Technique [2]} have been used to measure the stylistic similarity between generated artifacts \(\mathcal {G} = \lbrace \mathcal {G}_1,...,\mathcal {G}_m\rbrace \)  and a particular style \(\mathcal {C}\)  [3]}, [4]}. Objective measures have also been used to evaluate SI systems. Dong et al. measure the ratio of empty bars, pitch class diversity, note duration, rhythmic consistency, and tonal distance [5]}. Trieu and Keller propose a variety of metrics ranging from rhythmic variety to harmonic consistency [6]}. Since these metrics produce a single scalar value, it is easy to compare \(\mathcal {C}\)  and \(\mathcal {G}\) . However, these high-level metrics are likely only capable of measuring stylistic similarity in a very general sense. Sturm and Ben-Tal. plot distributions of meter, mode, number of tokens, pitch and pitch class for \(\mathcal {C}\)  and \(\mathcal {G}\) , but do not provide an automated method for analyzing discrepancies [7]}.
